TrendEcon: real-time economic indicators based on Google searches
Under the extraordinary circumstances caused by the Covid19 pandemic, the economy is moving too fast for the usual indicators we use to monitor economic activity. As a solution, we provide a set of economic indicators for Switzerland based on Google search trends. While standard economic indicators such as the consumer sentiment index, GDP, or private consumption are available with a lag of 3 months or more, we update our Google search based indicators daily. More on how to use our indicators.
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The problem: we lack timely economic data
Official economic statistics are usually released with a considerable lag. For example, the consumer sentiment index, GDP, or private consumption data become available with a lag of several months. The pace at which economic conditions are currently changing, however, requires more timely economic indicators in order to monitor and forecast economic activity. Economists have come up with different innovative ways to monitor the economy based on daily data, e.g. using daily electricity consumption.
Our solution: indicators based on Google Trends
To provide a set of timely economic indicators, we source Google Trends data. These indicators are available on a daily basis. The idea is that people’s searches on Google tell a lot about their perception of the state of the economy and demand for certain products and services.
When people become unemployed, for example, they start searching for local unemployment agencies (called “RAV” in German). When people want to buy clothes, they likely type the name of fashion stores like “H&M”, “Zara”, or “Zalando”. Changes in these searches will then tell us something about unemployment or the demand for clothing.
These indicators provide insights about the abrupt economic changes we are currently experiencing and will likely be among the first to capture changes once measures to fight the spread of Covid19 are lifted step by step. They will thus help to monitor the recovery and possibly indicate lasting changes in consumption habits.
Our indicators focus on private consumption because i) of its overall importance for economic growth: private consumption makes up over 60% of Swiss GDP; ii) in this crisis, private consumption is hit hardest: due to closures of restaurants, stores, cinemas etc. private consumption is severely limited. This situation is very different to a financial crisis like the one that occurred in 2008/2009.
How accurate are these indicators?
To ensure that our combinations of keywords lead to meaningful results, we compare our indicators to existing measures, namely the consumer sentiment index, GDP, and private consumption components whenever this is useful. Generally, the indicators we constructed broadly coincide with existing economic time series over the past 13 years, including the recession in 2009. However, note that our indicators are not an attempt of replicating or replacing any existing time series.
Limitations
The relationship between these search-based indicators and economic activity seems apparent. We believe that these indicators will provide useful during the whole economic roller-coaster ride that lies ahead of us, during the current downturn as well as the upswing(s) when things go slowly back to (a new?) normal. Note however, that the relationship between Google searches for specific keywords and real economic activity may change over time. First, the popularity of specific internet platforms and online stores can change, and that case Google searches and consumption behavior can change too. Second, this crisis is very different to previous ones as private demand drops largely because of mandated closures of restaurants, cinemas and stores to fight the spread of Covid19. Third, the crisis itself might lead to permanent changes in search behavior. For example, containment measures may lead permanently to a much larger proportion of the population to use the internet for grocery shopping. While there are currently two major supermarkets offering online shopping, people might start to search more and more for other shops offering this service.
FAQ’s
Why are these indicators different than just using Google Trends?
On Google Trends, you will find series based on a random sample of Google searches. Depending on the time frame you choose, Google returns daily, weekly, or monthly data. We downloaded the data many times to construct long-run data with a daily frequency. We further adjust the data for seasonal patterns in searches. It is normal that searches for gardening increase in spring. To make meaningful comparisons over time, these seasonal patterns are removed. Finally, our indicators are not based on one single keyword but several keywords are aggregated into one indicator. See Methods for further details. XXX LINK TO METHODS
Why did you use exactly these few keywords?
We carefully selected keywords based on assumptions on consumer behavior. We try to stick to those keywords that are most likely to reflect the intention to consume certain types of goods. You’ll probably still find that not every keyword that one might think of went into our indicator. This is due to the following reasons: First, to ensure privacy, Google does not return search trends based on too few searches. Some keywords are therefore censored and return a lot of zeros. Second, other keywords do not show any significant changes over time that coincide with economic activity or changes in demand. These keywords contain no relevant information to go into our indicators. Finally, more is not always better. We use those keywords that correlate strongest with real economic activity.
Why did you use exactly these few keywords?
We carefully selected keywords based on assumptions on consumer behavior. We try to stick to those keywords that are most likely to reflect the intention to consume certain types of goods. You’ll probably still find that not every keyword that one might think of went into our indicator. This is due to the following reasons: First, to ensure privacy, Google does not return search trends based on too few searches. Some keywords are therefore censored and return a lot of zeros. Second, other keywords do not show any significant changes over time that coincide with economic activity or changes in demand. These keywords contain no relevant information to go into our indicators. Finally, more is not always better. We use those keywords that correlate strongest with real economic activity.
Why do you use only German keywords?
For 63% of the population in Switzerland German is their main language. Search trends on Google are likely to be representative for the whole economy. Indeed, this is what we find if we compare our indicators to the existing target indicators like consumer sentiment. Due to Google’s privacy restrictions, searches in French and Italian within Switzerland are more often to be censored than German ones. If keywords are censored, Google replaces observations with a zero and we cannot use the keyword. This is another reason why we opt for using names of stores or brands: these do not change depending on the language of the user.
How reliable are these indicators?
We put a lot of effort into constructing daily, seasonally adjusted indicators that correlate with existing economic indicators. They can be used to say something about the evolution of demand for certain consumption categories. However, they remain indicators. We do not measure true economic activity as in number of t-shirts sold on a specific day or money spent on gardening equipment. Also note that this is an experiment in real time. If the correlation between search behavior and consumer demand changes, our indicators may improve or get worse in terms of tracking consumer demand.
What do these indicators not tell us?
XXX THIS CAN BE ANSWERED BEST ONCE WE HAVE THE SCALE / INTERPRETATION OF THE INDICATORS AND KNOW WHICH INDICATORS WE SHOW. THEN IT CAN BE EXPLAINED WITH AN EXAMPLE
How can I work with the data?
XXX DESCRIBE HOW THE DATA CAN BE DOWNLOADED? ANNOUNCE THAT CODE WILL BE AVAILABLE ON GITHUB?
Contributors
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